Selective serotonin reuptake inhibitors
(SSRIs) are the most commonly prescribed anti-depressants, but they don't work
What's more, patients must often try several
different SSRI medications, each with a different set of side effects, before finding
one that is effective. It takes three to four weeks to see if a particular
anti-depressant drug works. Meanwhile, patients and their families continue to
Now researchers at Tel Aviv University have
discovered a gene that may reveal whether people are likely to respond well to
SSRI anti-depressants, both generally and in specific formulations. The new
biomarker, once it is validated in clinical trials, could be used to create a
genetic test, allowing doctors to provide personalised treatment for
Doctoral students Keren Oved and Ayelet
Morag led the research under the guidance of Dr David Gurwitz of the
Department of Molecular Genetics and Biochemistry at TAU's Sackler Faculty of
Medicine and Dr Noam Shomron of the Department of Cell and Developmental
Biology at TAU's Sackler Faculty of Medicine and Sagol School of Neuroscience.
Sackler faculty members Prof. Moshe Rehavi
of the Department of Physiology and Pharmacology and Dr Metsada Pasmnik-Chor of
the Bioinformatics Unit were co-authors of the study, published in
"SSRIs only work for about 60% of
people with depression," said Dr Gurwitz of the Department of Molecular
Genetics and Biochemistry at Tel Aviv University’s Sackler Faculty. "A
drug from other families of antidepressants could be effective for some of the
others. We are working to move the treatment of depression from a
trial-and-error approach to a best-fit, personalised regimen."
news for depressed
More than 20 million Americans each year
suffer from disabling depression that requires clinical intervention. SSRIs
such as Prozac, Zoloft, and Celexa are the newest and the most popular
medications for treatment.
They are thought to work by blocking the re-absorption
of the neurotransmitter serotonin in the brain, leaving more of it available to
help brain cells send and receive chemical signals, thereby boosting mood. It
is not currently known why some people respond to SSRIs better than others.
To find genes that may be behind the
brain's responsiveness to SSRIs, the researchers first applied the SSRI
Paroxetine – brand name Paxil – to 80 sets of cells, or "cell lines",
from the National Laboratory for the Genetics of Israeli Populations, a bio
bank of genetic information about Israeli citizens.
The TAU researchers then analysed and
compared the RNA profiles of the most and least responsive cell lines. A gene
called CHL1 was produced at lower levels in the most responsive cell lines and
at higher levels in the least responsive cell lines. Using a simple genetic
test, doctors could one day use CHL1 as a biomarker to determine whether or not
to prescribe SSRIs.
The goal is to end up with a blood test
that will allow doctors to tell a patient which drug is best for him or her.
Repair of dysfunctional signalling
The TAU researchers also wanted to
understand why CHL1 levels might predict responsiveness to SSRIs. To this end,
they applied Paroxetine to human cell lines for three weeks – the time it takes
for a clinical response to SSRIs.
They found that Paroxetine caused increased
production of the gene ITGB3 – whose protein product is thought to interact
with CHL1 to promote the development of new neurons and synapses. The result is
the repair of dysfunctional signalling in brain regions controlling mood, which
may explain the action of SSRI antidepressants.
This explanation differs from the
conventional theory that SSRIs directly relieve depression by inhibiting the re-absorption
of the neurotransmitter serotonin in the brain.
Shomron adds that the new explanation resolves the longstanding mystery as to
why it takes at least three weeks for SSRIs to ease the symptoms of depression
when they begin inhibiting re-absorption after a couple days – the development
of neurons and synapses takes weeks, not days.
The TAU researchers are working to confirm
their findings on the molecular level and with animal models. Adva Hadar, a
master's student in Dr Gurwitz's lab, is using the same approach to find
biomarkers for the personalized treatment of Alzheimer's disease.